# from torch.utils.checkpoint import checkpoint
#
# import ldm.modules.attention
# import ldm.modules.diffusionmodules.openaimodel
#
#
# def BasicTransformerBlock_forward(self, x, context=None):
#     return checkpoint(self._forward, x, context)
#
#
# def AttentionBlock_forward(self, x):
#     return checkpoint(self._forward, x)
#
#
# def ResBlock_forward(self, x, emb):
#     return checkpoint(self._forward, x, emb)
#
#
# stored = []
#
#
# def add():
#     if len(stored) != 0:
#         return
#
#     stored.extend([
#         ldm.modules.attention.BasicTransformerBlock.forward,
#         ldm.modules.diffusionmodules.openaimodel.ResBlock.forward,
#         ldm.modules.diffusionmodules.openaimodel.AttentionBlock.forward
#     ])
#
#     ldm.modules.attention.BasicTransformerBlock.forward = BasicTransformerBlock_forward
#     ldm.modules.diffusionmodules.openaimodel.ResBlock.forward = ResBlock_forward
#     ldm.modules.diffusionmodules.openaimodel.AttentionBlock.forward = AttentionBlock_forward
#
#
# def remove():
#     if len(stored) == 0:
#         return
#
#     ldm.modules.attention.BasicTransformerBlock.forward = stored[0]
#     ldm.modules.diffusionmodules.openaimodel.ResBlock.forward = stored[1]
#     ldm.modules.diffusionmodules.openaimodel.AttentionBlock.forward = stored[2]
#
#     stored.clear()
#
